2,633 research outputs found

    Bound-state beta-decay of a neutron in a strong magnetic field

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    The beta-decay of a neutron into a bound (pe)(pe^-) state and an antineutrino in the presence of a strong uniform magnetic field (B1013B \gtrsim 10^{13} G) is considered. The beta-decay process is treated within the framework of the standard model of weak interactions. A Bethe-Salpeter formalism is employed for description of the bound (pe)(pe^-) system in a strong magnetic field. For the field strengths 101310^{13} GB1018 \lesssim B \lesssim10^{18} G the estimate for the ratio of the bound-state decay rate wbw_b and the usual (continuum-state) decay rate wcw_c is derived. It is found that in such strong magnetic fields wb/wc0.10.4w_b/w_c \sim 0.1-0.4. This is in contrast to the field-free case, where wb/wc4.2×106w_b/w_c \simeq 4.2 \times 10^{-6} [J. N. Bahcall, Phys. Rev. {\bf 124}, 495 (1961); L. L. Nemenov, Sov. J. Nucl. Phys. {\bf 15}, 582 (1972); X. Song, J. Phys. G: Nucl. Phys. {\bf 13}, 1023 (1987)]. The dependence of the ratio wb/wcw_b/w_c on the magnetic field strength BB exhibits a logarithmic-like behavior. The obtained results can be important for applications in astrophysics and cosmology.Comment: 22 pages (revtex4), 1 figure; v2: more detailed discussion on astrophysical applications in conclusion section, accepted for publication in Phys. Rev.

    Reduction of a metapopulation genetic model to an effective one island model

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    We explore a model of metapopulation genetics which is based on a more ecologically motivated approach than is frequently used in population genetics. The size of the population is regulated by competition between individuals, rather than by artificially imposing a fixed population size. The increased complexity of the model is managed by employing techniques often used in the physical sciences, namely exploiting time-scale separation to eliminate fast variables and then constructing an effective model from the slow modes. Remarkably, an initial model with 2D\mathcal{D} variables, where D\mathcal{D} is the number of islands in the metapopulation, can be reduced to a model with a single variable. We analyze this effective model and show that the predictions for the probability of fixation of the alleles and the mean time to fixation agree well with those found from numerical simulations of the original model.Comment: 16 pages, 4 figures. Supplementary material: 22 pages, 3 figure

    Pressure-Tuned Collapse of the Mott-Like State in Ca_{n+1}Ru_nO_{3n+1} (n=1,2): Raman Spectroscopic Studies

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    We report a Raman scattering study of the pressure-induced collapse of the Mott-like phases of Ca_3Ru_2O_7 (T_N=56 K) and Ca_2RuO_4 (T_N=110 K). The pressure-dependence of the phonon and two-magnon excitations in these materials indicate: (i) a pressure-induced collapse of the antiferromagnetic (AF) insulating phase above P* ~ 55 kbar in Ca_3Ru_2O_7 and P* ~ 5-10 kbar in Ca_2RuO_4, reflecting the importance of Ru-O octahedral distortions in stabilizing the AF insulating phase; and (ii) evidence for persistent AF correlations above the critical pressure of Ca_2RuO_4, suggestive of phase separation involving AF insulator and ferromagnetic metal phases.Comment: 3 figure

    Assessment of surface wind datasets for estimating offshore wind energy along the Central California Coast

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    In the United States, Central California has gained significant interest in offshore wind energy due to its strong winds and proximity to existing grid connections. This study provides a comprehensive evaluation of near-surface wind datasets in this region, including satellite-based observations (QuikSCAT, ASCAT, and CCMP V2.0), reanalysis (NARR and MERRA), and regional atmospheric models (WRF and WIND Toolkit). This work highlights spatiotemporal variations in the performance of the respective datasets in relation to in-situ buoy measurements using error metrics over both seasonal and diurnal time scales. The two scatterometers(QuikSCAT and ASCAT) showed the best overall performance, albeit with significantly less spatial and temporal resolution relative to other datasets. These datasets only slightly outperformed the next best dataset (WIND Toolkit), which has significantly greater temporal and spatial resolution as well as estimates of winds aloft. Considering tradeoffs between spatiotemporal resolution of the underlying datasets, error metrics relative to in-situ measurements, and the availability of data aloft, the WIND Toolkit appears to be the best dataset for this region. The framework and tradeoff analysis this research developed and demonstrated to assess offshore wind datasets can be applied in other regions where offshore wind energy is being considered

    Optimal discrete stopping times for reliability growth tests

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    Often, the duration of a reliability growth development test is specified in advance and the decision to terminate or continue testing is conducted at discrete time intervals. These features are normally not captured by reliability growth models. This paper adapts a standard reliability growth model to determine the optimal time for which to plan to terminate testing. The underlying stochastic process is developed from an Order Statistic argument with Bayesian inference used to estimate the number of faults within the design and classical inference procedures used to assess the rate of fault detection. Inference procedures within this framework are explored where it is shown the Maximum Likelihood Estimators possess a small bias and converges to the Minimum Variance Unbiased Estimator after few tests for designs with moderate number of faults. It is shown that the Likelihood function can be bimodal when there is conflict between the observed rate of fault detection and the prior distribution describing the number of faults in the design. An illustrative example is provided

    Tradeoff between short-term and long-term adaptation in a changing environment

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    We investigate the competition dynamics of two microbial or viral strains that live in an environment that switches periodically between two states. One of the strains is adapted to the long-term environment, but pays a short-term cost, while the other is adapted to the short-term environment and pays a cost in the long term. We explore the tradeoff between these alternative strategies in extensive numerical simulations, and present a simple analytic model that can predict the outcome of these competitions as a function of the mutation rate and the time scale of the environmental changes. Our model is relevant for arboviruses, which alternate between different host species on a regular basis.Comment: 9 pages, 3 figures, PRE in pres

    Finite-size scaling of the error threshold transition in finite population

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    The error threshold transition in a stochastic (i.e. finite population) version of the quasispecies model of molecular evolution is studied using finite-size scaling. For the single-sharp-peak replication landscape, the deterministic model exhibits a first-order transition at Q=Qc=1/aQ=Q_c=1/a, where Q% Q is the probability of exact replication of a molecule of length LL \to \infty, and aa is the selective advantage of the master string. For sufficiently large population size, NN, we show that in the critical region the characteristic time for the vanishing of the master strings from the population is described very well by the scaling assumption \tau = N^{1/2} f_a \left [ \left (Q - Q_c) N^{1/2} \right ] , where faf_a is an aa-dependent scaling function.Comment: 8 pages, 3 ps figures. submitted to J. Phys.

    Schwinger Boson Formulation and Solution of the Crow-Kimura and Eigen Models of Quasispecies Theory

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    We express the Crow-Kimura and Eigen models of quasispecies theory in a functional integral representation. We formulate the spin coherent state functional integrals using the Schwinger Boson method. In this formulation, we are able to deduce the long-time behavior of these models for arbitrary replication and degradation functions. We discuss the phase transitions that occur in these models as a function of mutation rate. We derive for these models the leading order corrections to the infinite genome length limit.Comment: 37 pages; 4 figures; to appear in J. Stat. Phy
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